Description Usage Arguments Details Value Author(s) References Examples
This function computes the standard two sample T-Test, as well as performing hypothesis tests and computing confidence intervals for the equality of both population means.
1 |
X |
A vector of observed values of a continuous random variable. |
Y |
A vector of observed values of a continuous random variable. |
alpha |
The desired Type I Error Rate for Confidence Intervals |
pooled |
Logical: If TRUE, a pooled estimate of the variance is used. That is, the variance is assumed to be equal in both groups. If FALSE, the Satterthwaite estimate of the variance is used. |
digits |
Number of Digits to round calculations |
This function performs the simple two-sample T-Test, while providing detailed information regarding the analysis and summary information for both groups. Note that this function requires the input of two vectors, so if the data is stored in a matrix, it must be separated into two distinct vectors, X and Y.
nx |
The number of observations in X. |
ny |
The number of observations in Y. |
mean.x |
The sample mean of X. |
mean.y |
The sample mean of Y. |
s.x |
The standard deviation of X. |
s.y |
The standard deviation of Y. |
d |
The difference between sample means, that is, mean.x - mean.y. |
s2p |
The pooled variance, when applicable. |
df |
The degrees of freedom for the test. |
TStat |
The test statistic for the null hypothesis mu_X - mu_Y = 0. |
p.value |
The P-value for the test statistic for mu_X - mu_Y = 0. |
CIL |
The lower bound of the constructed confidence interval for mu_X - mu_Y = 0. |
CIU |
The lower bound of the constructed confidence interval for mu_X - mu_Y = 0. |
pooled |
Logical: as above for assuming variances are equal. |
alpha |
The desired Type I Error Rate for Confidence Intervals |
Michael Rotondi, mrotondi@yorku.ca
Casella G and Berger RL. Statistical Inference (2nd Ed.) Duxbury: New York, 2002.
Szklo M and Nieto FJ. Epidemiology: Beyond the Basics, Jones and Bartlett: Boston, 2007.
1 2 3 |
Epidemiological T-Test Analysis
Number of Observations in Group I: 100
Sample Mean for Group I: 9.882 with a sample standard deviation of 1.063
Number of Observations in Group II: 100
Sample Mean for Group II: -0.118 with a sample standard deviation of 0.952
Sample Difference Between Means: 10
95% Confidence Limits for true mean difference: [9.719, 10.282]
T-Statistic for H0: difference = 0 vs. HA: difference != 0 is 70.104 with a p.value of 0
Note: The above Analysis uses the Satterthwaite estimate of the variance.
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